Hosang Jung

1. Recent research highlights the substantial risks associated with prolonged worker fatigue across multiple industries, including increased injuries, elevated stress and reduced performance [1–4]....

This study explores the evolving trends and research issues in the field of drone-assisted multimodal logistics over the past two decades. By employing various text-mining techniques on related research publications, we identify the most frequently investigated topics and research issues within this domain. Specifically, we utilize titles, abstracts, and keywords from the collected studies to perform both Latent Dirichlet Allocation techniques and Term Frequency-Inverse Document Frequency analysis, which help in identifying latent topics and the core research themes within the field. Our analysis focuses on three primary categories of drone-assisted logistics: drone–truck, drone–ship, and drone–robot systems. The study aims to uncover which latent topics have been predominantly emphasized in each category and to highlight the distinct differences in research focuses among them. Our findings reveal specific trends and gaps in the existing literature, providing a clear roadmap for future research directions in drone-assisted multimodal logistics. This targeted analysis not only enhances our understanding of the current state of the field but also identifies critical areas that require further investigation to advance the application of drones in logistics.

This study focuses on the process of tailoring work schedules for warehouse workers by incorporating their perceived physical fatigue levels. Recognizing the importance of understanding and mitigating workplace fatigue, we present a practical and cost-effective methodological framework. Our approach integrates survey-based fatigue measurements, regression analysis, and mathematical optimization modeling. In the case company, order pickers in a South Korean order fulfillment center were surveyed, followed by regression analysis identifying six important factors for tailoring work schedules to manage fatigue. The optimization model, linked with the regression analysis, determines the timing and duration of work and break cycles. Four distinct schedules are generated, balancing the goals of minimizing workers' average and final fatigue levels. After consultation with the center manager, a schedule focusing on reducing workers' final fatigue is approved. The new schedule reduces workers’ mean final fatigue levels by 11.5% while maintaining the same total working hours.

With the development of robot technology, trials adopting robots for last-mile delivery are continuing, and the final destination of last-mile delivery is further expanding into indoor environments. Unlike existing studies conducted for robot-based last-mile delivery in outdoor environments, two main issues must be solved to enable last-mile delivery in indoor environments using robots. First, it is necessary to reasonably and realistically estimate the robot travel time considering horizontal and vertical movement segments within a given building. Second, optimizing the robot routing problem based on the estimated robot travel time is necessary. In this paper, we proposed a new method to estimate the robot travel time considering robot movement characteristics and an elevator in a building. In addition, we developed a mathematical model of the robot routing problem and problem-specific heuristic based on a genetic algorithm to quickly solve the proposed mathematical model. It obtained the exact solutions when the problem size was small and near-optimal solutions in the medium- and large-sized problems (average optimality gap: 0.11% and 0.18%, respectively). Through extensive experiments assuming various building structures, it was determined that the proposed model and heuristic can quickly yield realistic solutions for indoor robot-based last-mile delivery.

Asset management is not new, and research has been conducted in private and public sectors on how to systematically maintain infrastructure or facilities for sustainable use and achieve the level of service desired by users or customers at the lowest life cycle costs. This research identifies the research topics and trends in asset management over the past 30 years. To this end, latent Dirichlet allocation, a topic modeling approach, was applied to articles published in engineering journals and investigated the following three research questions: (1) what have the key topics been for the past three decades? (2) what are the main activities and target sectors of asset management? (3) how have the research topics and keywords changed over the past three decades? The analysis shows that the target field of asset management has broadened while the main activities of asset management have been limited to several popular activities such as life cycle cost analysis and reliability analysis. Some implications and future research directions are also discussed.

In general, the demand for delivery cannot be fulfilled efficiently due to the excessive traffic in dense urban areas. Therefore, many innovative concepts for intelligent transportation of freight have recently been developed. One of these concepts relies on drone-based parcel delivery using rooftops of city buildings. To apply drone logistics system in cities, the operation design should be adequately prepared. In this regard, a mixed integer programming model for drone operation planning and a heuristic based on block stacking are newly proposed to provide solutions. Additionally, numerical experiments with three different problem sizes are conducted to check the feasibility of the proposed model and to assess the performance of the proposed heuristic. The experimental results show that the proposed model seems to be viable and that the developed heuristic provides very good operation plans in terms of the optimality gap and the computation time.